Open Science Research Excellence
%0 Journal Article
%A Yiannis G. Smirlis 
%D 2018 
%J  International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 138, 2018
%T Classifying and Predicting Efficiencies Using Interval DEA Grid Setting
%U http://waset.org/publications/10009165
%V 138
%X The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.
%P 119 - 123